Two-dimensional warping for one-dimensional signals - Conceptual framework and application to ECG processing

Martin Schmidt, Mathias Baumert, Alberto Porta, Hagen Malberg, Sebastian Zaunseder

Research output: Contribution to journalArticlepeer-review


We propose a novel method for evaluating the similarity between two 1d patterns. Our method, referred to as two-dimensional signal warping (2DSW), extends the basic ideas of known warping techniques such as dynamic time warping and correlation optimized warping. By employing two-dimensional piecewise stretching 2DSW is able to take into account inhomogeneous variations of shapes. We apply 2DSW to ECG recordings to extract beat-to-beat variability in QT intervals (QTV) that is indicative of ventricular repolarization lability and typically characterised by a low signal-to-noise ratio. Simulation studies show high robustness of our approach in presence of typical ECG artefacts. Comparison of short-term ECG recorded in normal subjects versus patients with myocardial infarction (MI) shows significantly increased QTV in patients (normal subject 2.36 ms \pm 1.05 ms vs. MI patients 5.94 ms \pm 5.23 ms (mean \pm std), p

Original languageEnglish
Article number6891378
Pages (from-to)5577-5588
Number of pages12
JournalIEEE Transactions on Signal Processing
Issue number21
Publication statusPublished - Nov 1 2014


  • Dynamic time warping
  • ECG
  • QT
  • QT interval
  • QT variability
  • signal processing
  • two-dimensional warping
  • warping

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing


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